Instructions to use clone147/urvemodel1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use clone147/urvemodel1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Voicelab/trurl-2-13b") model = PeftModel.from_pretrained(base_model, "clone147/urvemodel1") - Notebooks
- Google Colab
- Kaggle
Download config.json from clone147/urvemodel1: direct link, hf CLI and curl.
- Browser
- Download file 1.09 kB
-
https://huggingface.co/clone147/urvemodel1/resolve/main/config.json
- Command line
-
hf download hf://clone147/urvemodel1/config.json
-
curl -L -o config.json https://huggingface.co/clone147/urvemodel1/resolve/main/config.json
1.09 kB
| { | |
| "_name_or_path": "Voicelab/trurl-2-13b", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 5120, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 13824, | |
| "max_position_embeddings": 4096, | |
| "model_type": "llama", | |
| "num_attention_heads": 40, | |
| "num_hidden_layers": 40, | |
| "num_key_value_heads": 40, | |
| "pad_token_id": 0, | |
| "pretraining_tp": 1, | |
| "quantization_config": { | |
| "bnb_4bit_compute_dtype": "float16", | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_use_double_quant": true, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": null, | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": false, | |
| "load_in_8bit": true, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.37.1", | |
| "use_cache": false, | |
| "vocab_size": 32001 | |
| } | |